Iterative methods have been greatly influential in continuous optimization. In fact, almost all algorithms in that field are iterative in nature. Recently, a confluence of ideas from optimization and theoretical computer science has led to breakthroughs in terms of new understanding and running time bound improvements for some of the classic iterative continuous optimization primitives. In this workshop we explore these advances as well as new directions that they have opened up. Some of the specific topics that this workshop plans to cover are: advanced first-order methods (non-smooth optimization, regularization and preconditioning), structured optimization, fast LP/SDP solvers, advances in interior point methods and fast streaming/sketching techniques. One of the key themes that will be highlighted is how combining the continuous and discrete points of view can often allow one to achieve near-optimal running time bounds.

Enquiries may be sent to the organizers workshop_opt2 [at] lists [dot] simons [dot] berkeley [dot] edu (at this address).